Known Issues

We describe here several of the issues or characteristics that can be found on the VISTA data.

Contents

Bad pixels in detector number 1

Detector number 1 contains a series of bad pixels grouped in three large areas. They are clearly visible in the single pawprint images (see figure below). Depending on the number of jitters and pattern they can be masked out in the stack and or tile images. The example below is from njitter=2 and shows that they are still present in the stacked image. In such a case the bad pixel areas are filled in with the average sky background value.

Point-like objects in flat and sky frames

The figure shows a section of a flatfield (left) and sky (right) frames showing that these regions of different sensitivity do not all flatfield out completely.

Detector 16 variable QE

The QE of detector 16 varies on short timescales making accurate flatfielding impossible. The figure below shows a science image and its confidence map. The top half of the detector is more affected by this. In K band the effect is quite small but it is very noticeable in the bluer bands.

Bad channel in detector 6

Channel #14 was intermittently bad and affected some frames obtained before 20th of November 2009. It was fixed by swapping a video card. A side effect of this problem was an excess of spurious sources detected by the extraction software in the affected area. This also sometimes affected values like the average seeing or ellipticity in the frame (the frame seeing is sometimes derived as zero or negative in these cases). Data obtained after that date does not present this problem.

Filter wheel out of position

In some cases the filter wheel does not position itself in the correct
location and produces variable vignetting due to out of focus "dust" particles on the filters. These are visible
in the sky frames on the left as a "moving" doughnut-like shapes and the vertical dark band near the right-hand edges.

The figure on the left shows four different detectors of the same sky frame (click on the figure for a larger version). Note that the amount of vignetting is not the same in all chips since the filter wheel is rotated with respect to the detector array.

The effect of the filter wheel out of position is barely visible on the science images but results in a change of sensitivity in the affected area so inspection of sky frames is advisable.

The vertical bands visible in the upper two sky frames are the 16 readout channels. Since these all have slightly different measured and computed linearity corrections, small errors in the correction can show up as level changes in sky. The gross effect of these on science product images is removed during sky subtraction but the residual small sensitivity (gain) correctionimplied (<1%) will still be present.

Detector #4

This detector has a number of bad rows visible near the bottom that do not always correct very well during the standard image processing applied to VISTA data.

Spurious detections around bright stars

Bright saturated stars produce local maxima around them which are interpreted as detections from the extraction software. The figure below shows three images in three different filters of the same bright star with detections overplotted (blue: stellar like, green: extended, red: noise). There is nothing that can be done in the single band catalogues to flag these detections but note that these spurious objects are typically classified as extended and many of them have large ellipticities. When doing a bandmerge they result in objects detected in only one band so a good algorithm to remove or flag them is to search for extended objects around bright stars (search radius depending on brightness of star) and flag objects detected in only one band.

Saturated objects also have a "hole" in their centre visible as a dark spot in the images. This is due to the double correlated sampling used during image readout. Since there is no shutter in the camera the delivered image is the difference between two on-sky exposures. If the centre of star if bright enought to saturate the first of these (the reset image equivalent to a ~1s exposure) then a "hole" will appear in the middle of the delivered image of the star.

Images with large ellipticities

Images with large average ellipticity (larger than 0.2) are either due to the telescope being out of focus or the telescope moving while taking the exposure.

The figure on the left (click for a larger version) shows a trailed image from one detector of one exposure obtained while the telescope was moving. Objects marked in blue have been classified as stellar like and show an average ellipticity of 0.4.

Below a zoom on another similar image.

Persistance

The persistance in VIRCAM is minimal. For examples click on the following link.

Tile images variable depth

The figure below shows a tile image (left) and its confidence map (right). The confidence map encodes the relative exposure levels in each pixel as well as bad pixels and sensitivity variations. The effects of bad pixels in detector 1 (bottom left), detector 4 (bottom right) and detector 16 (top right) along with some bad rows are clearly visible on it. Note also that 15% of the tile corresponding to the two edges along the vertical axis in the figure (the "ears") have only half the total effective exposure (the EXPTIME keyword in the images is correct for the whole tile; the main effect is variable noise in areas of different effective exposure time).